In the simulation system as described above, any item included in the total combined energy is preferably approximated to a target value to a high accuracy. The reason is that if any item can be approximated to the target value, it is possible to accurately assess an operation, and it becomes easy to execute a plan for energy conservation and the reduction of an environmental load. Well-known techniques related to such a system are those disclosed in the Patent Literature 1 through 7 listed below, for example.
A system for simulating an air conditioner disclosed in Patent Literature 1 constructs a model by individually combining dummy elements that represent heat and power supply devices. The dummy elements are individually combined by causing the corresponding dummy elements included in a second cell group to refer to each other. Thus, to construct a model, expertise is required to at least determine the combination relationships between, and the combination order of, the heat and power supply devices, and it is impossible to easily start a simulation. Further, external conditions such as “an outdoor air wet-bulb temperature, the amount of air flow, and a coil inlet/outlet air temperature” are provided so as to make convergent calculations for a variation caused in the input/output relationships between the dummy elements in a function in the constructed model. Thus it is not at all taken into account that operating conditions are obtained in accordance with a target value of a heat load that is actually required.
A system for optimizing heat and power supply disclosed in Patent Literature 2 sets an objective function, and makes optimization with the provision of a facility constraint and a supply-demand balance constraint, so as to obtain an optimal scale, an optimal operation pattern, a shadow price, and an energy unit price, of a device. Thus it is impossible for a user to manually and freely set the configuration of a device and an operating state. This is also true of: Patent Literature 3 and 4, which use a genetic algorithm; Patent Literature 5, which relates to the minimization of the costs of cogeneration; Patent Literature 6, which relates to the determination of whether an electric-power-preferential operation or a heat-load-preferential operation is to be performed; and Patent Literature 7, which relates to selection from an existing energy generation facility.
In addition, in the system of each of the Patent Literature, the definitions of heat and power supply devices are individually set, and these definitions are highly complex. Further, a nonlinear relationship exists between at least two types of energies that correspond to items of the total combined energy, and therefore programming for obtaining operating conditions that satisfy all the complex definitions of the relationships between a plurality of the devices is more complex and unrealistic. To solve these problems, some of the Patent Literature use a genetic algorithm (Patent Literature 3 and 4), and the phased setting of a load factor, such as 25%, 50%, and 75% (Patent Literature 5). Consequently, it is impossible to set operating conditions in accordance with an arbitrary load factor, and it is impossible to obtain operating conditions in accordance with an actual situation.
Citation List
[Patent Literature]
[PTL 1] Japanese Laid-Open Patent Publication No. 2006-226572
[PTL 2] Japanese Laid-Open Patent Publication No. 2002-227721
[PTL 3] Japanese Laid-Open Patent Publication No. 2004-318824
[PTL 4] Japanese Laid-Open Patent Publication No. 11-39004
[PTL 5] Japanese Laid-Open Patent Publication No. 8-200155
[PTL 6] Japanese Laid-Open Patent Publication No. 2002-295308
[PTL 7] Japanese Laid-Open Patent Publication No. 2003-67456